What are some real-world examples of regularization in machine learning?

What are some real-world examples of regularization in machine learning?

Regularization is used to prevent overfitting in models. For instance, in finance, Lasso regression helps in selecting important features for predicting stock prices.

Can you explain how Lasso regression works?

Lasso regression adds a penalty equal to the absolute value of the magnitude of coefficients to the loss function, which helps in feature selection.

Are there other types of regularization?

Yes, besides Lasso, there's Ridge regression, which adds a penalty equal to the square of the coefficients, and Elastic Net, which combines both.

How does regularization affect model performance?

Regularization can improve model performance on unseen data by reducing overfitting, leading to better generalization.

Can you give an example of regularization in image processing?

In image processing, regularization techniques like Tikhonov regularization are used to enhance image reconstruction and denoise images.